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1.1. Introduction
1.2. Definition of Distributed Systems
1.3. Significant Consequences of Distributed Systems
1.4. Goals of Distributed Systems
1.5. Issues of Distributed Systems
1.6. Types of Distributed Systems
1.6.1. Distributed Computing system
1.6.2. Distributed information systems
1.6.3. Distributed pervasive system:
1.7. Distributed System Models
1.7.1. Architectural Model:
1.7.2. Interaction Model:
1.7.3. Fault Models
1.7.4. Security Model
1.8. Hardware Concept
1.8.1. Multiprocessor System
1.8.2. Multicomputer System
1.9. Software Concept
1.9.1. Distributed Operating System
1.9.2. Network Operating System
1.9.3. Middleware
1.10. Services offered by Middleware
1.11. Models of Middleware
1.11.1. Remote Procedure Call (RPC)
1.11.2. Message Oriented Middleware (MOM)
1.11.3. Distributed Object Technology
1.12. Client-Server Model
1.12.1. Client
1.12.2. Server
1.12.3. Network
Summary
Review Questions
2.1. Introduction
2.2. Layered Protocols
2.2.1. Seven Layers of OSI
2.3. Remote Procedure call
2.3.1. The RPC Model
2.3.2. Implementing RPC Mechanism
2.3.3. Parameter Passing in RPC
2.3.4. Extended RPC Models
2.3.5. Example of RPC
2.4. Remote Object Invocation
2.4.1. Types of Object and Binding
2.5. Remote Method Invocation
2.5.1. Architecture of Remote Method Invocation
2.5.2. Remote Method Invocation Process
2.6. Message-Oriented Communication
2.6.1. Types of Communication
2.6.2. Message-Oriented Transient Communication
2.6.3. Message-Oriented Persistent Communication
2.7. Group Communication
2.7.1. One – to - many communication
2.7.2. Many – to – one Communication
2.7.3. Many –to – many
2.8. Stream-Oriented Communication
Summary
Review Questions
3.1 Introduction: Clock Synchronization
3.2 Physical clock
3.2.1 Christian’s Algorithm
3.2.2 Berkeley Algorithm
3.2.3 Network Time Protocol
3.3 Logical clock
3.1.1 Lamport’s Scalar Clock
3.3.2 Vector Timestamp Ordering
3.4 Election algorithms
3.4.1 Bully Algorithm
3.4.2. Ring Algorithm
3.5 Mutual exclusion
3.6 Centralized algorithm
3.7 Distributed Mutual exclusion
3.7.1 Non-Token Based Algorithms
3.7.2 Token-Based Algorithms
3.7.3. Singhal’s Heuristic Algorithm
3.7.4 Raymond’s Tree-Based Algorithm
Summary
Review Questions
4.1 Resource Management in Distributed system
4.2 Desirable Features of global scheduling algorithm
4.3 Scheduling in the Distributed system
4.4 Taxonomy of the Distributed scheduling
4.4.1 Hierarchical Classification
4.4.2 Dynamic Scheduling Algorithm
4.5 Task assignment approach
4.6 Load balancing approach
4.6.1 Benefits of Load Balancing
4.6.2 Static Load Balancing
4.6.3 Dynamic Load Balancing
4.6.4 Comparison Between Static and Dynamic Load Balancing Algorithms
4.6.5 Static versus Dynamic Algorithms
4.6.6 Deterministic versus Probabilistic Algorithms
4.6.7 Centralized versus Distributed Algorithms
4.7 Issues in Designing Load balancing algorithm
4.7.1 Load Estimation Policy
4.7.2 Process Transfer Policy
4.7.3 Location Policies
4.7.4 State Information Exchange Policy
4.7.5 Priority Assignment Policy
4.8 Load sharing approach
4.8.1 Load Estimation Policy
4.9 Process Management
4.9.1 Threads
4.10 Virtualization
4.11 Clients
4.11.1 Thin-Client Network Computing
4.11.2 Client-Side Software for Distribution Transparency
4.12 Servers
4.12.1 General Design Issues
4.12.2 Cluster of Servers
4.12.3 Distributed Servers
4.13 Code Migration
4.13.1 Approaches to Code Migration
4.13.2 Models for Code Migration
4.13.3 Migration and Local Resources
4.13.4 Migration in Heterogeneous Systems
Summary
Review Questions
5.1. Introduction
5.2. Consistency
5.2.1 Consistency Models and their Evolution
5.2.1 Data-Centric Consistency Models
5.2.2 Client-Centric Consistency Models
5.3. Replication
5.3.1 Replica Location
5.3.2 Replication Models
5.3.3 Replica Consistency
5.4. Fault Tolerance
5.4.1 Failure Models
5.4.2 Failure Detection
5.4.3 Failure Masking
5.4.4 Resilience by Process Groups:
5.4.5 Reliable Communication: Client - Server
5.4.6 Reliable Group Communication:
5.4.7 Atomic Multicast
5.4.8 Recovery
Summary
Review Questions
6.1. Introduction to Distributed File systems
6.1.1 Features of a Good DFS
6.1.2 File Services
6.1.3 Naming
6.1.4 Naming Schemes
6.1.5 File Sharing Semantics
6.1.6 Caching
6.1.7 File Replication
6.2. Case Study on Distributed File Systems
6.2.1 NFS
6.2.2 Andrew File System
6.3.
Introduction to Name Services and Domain Name System
6.3.1 Name Service
6.3.2 The Domain Name System
6.4. Directory services
6.5. Case study: The Global Name Service
6.6. X.500 Directory Service
6.7. Google Case Study
6.7.1 Components of Google Infrastructure
Summary
Review Questions
Experiment No. 1
Experiment No. 2
Experiment No. 3
Experiment No. 4
Experiment No. 5
Experiment No. 6
Experiment No. 7
Experiment No. 8
Experiment No. 9
Experiment No. 10
Experiment No. 11
Experiment No. 12
Dr. Nupur Giri is Professor and Head of Department, Computer Engineering at Vivekanand Education Society Institute of Technology, Mumbai. She has more than 25 years of industry and teaching experiences. Her doctoral research was in the multidisciplinary field of Multi Agent System and Mobile Computing, typically Cellular Networks. Her contributions in the field of Artificial Intelligence, Mobile and Distributed Computing have been published in many journals and International conferences. She has filed many patents.
She is also a committee member of many international conferences. She is recognized PhD guide in University of Mumbai. She has represented India as an Expert in Worldskills-2011, London as well as in Worldskills-2013, Germany in the category of Web Design. She has also been awarded Microsoft's "AI for Earth" Grant in the year 2018.
Dr. Lata L. Ragha is Professor and Head, Department of Computer Engineering at Fr. C. Rodrigues Institute of Technology, Vashi, Navi-Mumbai. She has received her Ph. D. degree from Jadavpur University, Kolkata in 2011. Her research interests include in the areas of Networking, Security, Internet Routing, and Data Mining. She has more than 100 research publications in International Journals and conferences. She is having 32 years of teaching experience. She is a member of Board of Studies, Mumbai University. She is associated with two colleges as member of Department Advisory Board. Two members have received their PhD degree under her guidance and two more have submitted their thesis under her guidance.
Dr. Bhushan A Jadhav is an Assistant Professor at Thadomal Shahani Engineering College, Bandra, Mumbai. He has more than 11 years of teaching experience and has completed his Ph.D in area of Cloud Computing &Big Data Analytics. His area of interest and research includes cutting edge technologies such as DevOps, Internet of Things (IOT), Cloud Computing, Big Data Analytics, Python Programming, R Programming and Advance Information Security. He has published more than 8 research papers in National and International journals and conferences He has published six books with various publishers. He is certified trainer for Star Certification’s Python Programming, Cloud Computing and DevOps Courses.
